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data engineer

H2o Labs

Location: Onsite Shift: Night Shift Job Type: Full-TimeJob Overview:We are looking for a skilled and detail-oriented Data Engineer with 2&ndash;4 years of hands-on experience to join our growing team. The ideal candidate will be responsible for building, optimizing, and maintaining scalable data pipelines and architectures to support data-driven decision-making across the organization.Key Responsibilities:<ul><li>Design, develop, and maintain scalable ETL/ELT pipelines</li><li>Build and manage data warehouses and data lakes</li><li>Ensure data quality, integrity, and reliability across systems</li><li>Optimize and automate data workflows for performance and scalability</li><li>Collaborate with data analysts, scientists, and business stakeholders</li><li>Work with large datasets and ensure efficient data processing</li><li>Monitor and troubleshoot data-related issues</li><li>Implement data security and governance best practices</li><li>Communicate effectively with cross-functional teams and stakeholders</li></ul>Required Skills &amp; Qualifications:<ul><li>Bachelor&rsquo;s degree in Computer Science, IT, or related field</li><li>2&ndash;4 years of experience as a Data Engineer or similar role</li><li>Strong proficiency in SQL and database design</li><li>Hands-on experience with Python (or similar programming language)</li><li>Experience with ETL tools (e.g., Airflow, Talend, Informatica)</li><li>Familiarity with cloud platforms (AWS, GCP, or Azure)</li><li>Experience with big data tools (e.g., Hadoop, Spark)</li><li>Understanding of data warehousing concepts</li><li>Excellent communication and interpersonal skills</li><li>Strong problem-solving and analytical skills</li></ul>Preferred Qualifications:<ul><li>Experience with real-time data processing</li><li>Knowledge of Docker/Kubernetes</li><li>Familiarity with CI/CD pipelines</li><li>Experience working in agile environments</li></ul>Job Type: Full-timePay: Rs100,000.00 - Rs220,000.00 per monthWork Location: In person

Data Engineer

AlphaBOLD

<div><h2 class="jobSectionHeader">JOB SUMMARY</h2>

Alphabold is looking for a skilled Data Engineer with 3&ndash;5 years of experience to design, build, and maintain scalable data pipelines and infrastructure. The ideal candidate will have strong expertise in data processing, database systems, and cloud platforms, enabling efficient data flow and analytics across the organization.
<h3 class="jobSectionHeader">
Key Responsibilities</h3>
<ul><li>Design, develop, and maintain scalable ETL/ELT data pipelines</li>
<li>Build and optimize data architectures, data lakes, and data warehouses</li>
<li>Ensure data quality, integrity, and reliability across systems</li>
<li>Collaborate with data analysts, data scientists, and business stakeholders to deliver data solutions</li>
<li>Develop and manage batch and real-time data processing systems</li>
<li>Monitor and troubleshoot data pipeline performance and failures</li>
<li>Implement data governance, security, and compliance best practices</li>
<li>Automate workflows and improve data engineering processes</li>
</ul><h3 class="jobSectionHeader">Required Skills &amp; Qualifications</h3>
<ul><li>3&ndash;5 years of experience in data engineering or related roles</li>
<li>Strong proficiency in SQL and Python (or Scala/Java)</li>
<li>Hands-on experience with ETL tools and frameworks (e.g., Apache Airflow, Talend, Informatica)</li>
<li>Experience with big data technologies such as Apache Spark, Hadoop, or Kafka</li>
<li>Solid understanding of data warehousing concepts and modeling (Star/Snowflake schema)</li>
<li>Experience with cloud platforms like AWS, Azure, or Google Cloud</li>
<li>Familiarity with relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB)</li>
<li>Experience with version control systems (e.g., Git)</li>
</ul><h3 class="jobSectionHeader">Preferred Qualifications</h3>
<ul><li>Experience with containerization tools like Docker and orchestration tools like Kubernetes</li>
<li>Knowledge of CI/CD pipelines and DevOps practices</li>
<li>Familiarity with data visualization tools (e.g., Power BI, Tableau)</li>
<li>Understanding of streaming data systems and real-time analytics</li>
</ul><h3 class="jobSectionHeader">Soft Skills</h3>
<ul><li>Strong problem-solving and analytical skills</li>
<li>Good communication and collaboration abilities</li>
<li>Ability to work in a fast-paced, agile environment</li>
<li>Attention to detail and commitment to data accuracy</li>
</ul><h3 class="jobSectionHeader">Education</h3>
<ul><li>Bachelor&rsquo;s degree in Computer Science, Engineering, Information Technology, or a related field</li>
</ul><h3 class="jobSectionHeader">Nice to Have</h3>
<ul><li>Certifications in cloud platforms (AWS, Azure, GCP)</li>
<li>Experience working with large-scale distributed systems</li></ul></div>

Dubizzle Labs

<div>
 You will be participating in exciting projects covering the end-to-end data lifecycle &ndash; from raw data integrations with primary and third-party systems, through advanced data modeling, to state-of-the-art data visualization and development of innovative data products.
 
 
 You will have the opportunity to learn how to build and work with both batch and real-time data processing pipelines. You will work in a modern cloud-based data warehousing environment alongside a team of diverse, intense, and interesting co-workers. You will liaise with other departments &ndash; such as product &amp; tech, the core business verticals, trust &amp; safety, finance, and others &ndash; to enable them to be successful.
 
 
 
 Your Responsibilities
 
 
 
 <ul>
 <li>
 Design, implement and support data warehousing;
 </li>
 <li>
 Raw data integrations with primary and third-party systems
 </li>
 <li>
 Data warehouse modeling for operational &amp; application data layers
 </li>
 <li>
 Development in Amazon Redshift cluster
 </li>
 <li>
 SQL development as part of agile team workflow
 </li>
 <li>
 ETL design and implementation in Matillion ETL
 </li>
 <li>
 Real-time data pipelines and applications using serverless and managed AWS services such as Lambda, Kinesis, API Gateway, etc.
 </li>
 <li>
 Design and implementation of data products enabling data-driven features or business solutions
 </li>
 <li>
 Building data dashboards and advanced visualizations in Sisense for data cloud teams (formerly Periscope Data) with a focus on UX, simplicity, and usability
 </li>
 <li>
 Working with other departments on data products &ndash; i.e. product &amp; technology, marketing &amp; growth, finance, core business, advertising, and others
 </li>
 <li>
 Being part and contributing towards a strong team culture and ambition to be on the cutting edge of big data
 </li>
 <li>
 Evaluate and improve data quality by implementing test cases, alerts, and data quality safeguards
 </li>
 <li>
 Living the team values: Simpler. Better. Faster.
 </li>
 <li>
 Strong desire to learn
 
 
 
 </li>
 </ul>
 
 Required Minimum Experience (must)
 
 
 
 <ul>
 <li>
 1-3 years experience in data processing, analysis, and problem-solving with large amounts of data;
 </li>
 <li>
 Good SQL skills across a variety of relational data warehousing technologies especially in cloud data warehousing (e.g. Amazon Redshift, Google BigQuery, Snowflake, Vertica, etc.)
 </li>
 <li>
 1+ year of experience with one or more programming languages, especially Python
 </li>
 <li>
 Ability to communicate insights and findings to a non-technical audience
 </li>
 <li>
 Written and verbal proficiency in English
 </li>
 <li>
 Entrepreneurial spirit and ability to think creatively; highly-driven and self-motivated; strong curiosity and strive for continuous learning
 </li>
 <li>
 Top of class University technical degree such as computer science, engineering, math, physics.
 
 
 
 </li>
 </ul>
 
 Additional Experience (strong Plus)
 
 
 
 <ul>
 <li>
 Experience working with customer-centric data at big data-scale, preferably in an online / e-commerce context
 </li>
 <li>
 Experience with modern big data ETL tools (e.g. Matillion)
 </li>
 <li>
 Experience with AWS data ecosystem (or other cloud providers)
 </li>
 <li>
 Track record in business intelligence solutions, building and scaling data warehouses, and data modeling
 </li>
 <li>
 Tagging, Tracking, and reporting with Google Analytics 360
 </li>
 <li>
 Knowledge of modern real-time data pipelines (e.g. serverless framework, lambda, kinesis, etc.)
 </li>
 <li>
 Experience with modern data visualization platforms such as Periscope, Looker, Tableau, Google Data Studio, etc.
 </li>
 <li>
 Linux, bash scripting, Javascript, HTML, XML
 </li>
 <li>
 Docker Containers and Kubernete
 
 
 
 </li>
 </ul>
</div>

Senior / Lead / Data Engineer &ndash; Comprehensive Job DescriptionAbout the RoleWe are seeking a highly skilled and experienced Senior/Lead/Staff Data Engineer todesign, build, and maintain scalable, reliable, and high-performance data systems. Thisrole requires deep technical expertise, strong ownership of data platforms, and the abilityto lead cross-functional initiatives that power analytics, machine learning, businessintelligence, and mission-critical applications.You will play a key role in shaping data architecture, ensuring data quality and governance,and enabling teams across the organization to make data-driven decisions withconfidence.Key ResponsibilitiesData Architecture &amp; Modeling<ul><li>Design and implement scalable data models, including:</li></ul>o Star schema (fact and dimension tables)o Conceptual, logical, and physical data models<ul><li>Develop enterprise data warehouse solutions ensuring:</li></ul>o Flexibility, scalability, and performance optimization<ul><li>Define and enforce data modeling standards and best practices</li></ul>Data Engineering &amp; Pipeline Development<ul><li>Build and maintain end-to-end data pipelines:</li></ul>o Data ingestion &rarr; staging &rarr; transformation &rarr; serving layers<ul><li>Develop robust ETL/ELT processes using modern tools and frameworks</li><li>Implement:</li></ul>o Typed staging layerso Data validation pipelineso Safe backfill and replay mechanisms<ul><li>Optimize SQL queries, indexing strategies, and database performanceData Platform Reliability &amp; Observability</li><li>Own data pipeline reliability and integrity</li><li>Build observability systems, including:</li></ul>o Monitoring dashboardso Alerting frameworks (actionable, low-noise)o Data freshness tracking<ul><li>Implement:</li></ul>o Schema contracts and enforcemento Data quality checks and validation ruleso Failure detection in CI pipelines (not post-deployment)<ul><li>Lead incident management and root cause analysis</li></ul>Data Governance &amp; Quality<ul><li>Establish data governance frameworks:</li></ul>o Standards, policies, and best practices<ul><li>Enforce:</li></ul>o Data integrityo Data lineage and traceabilityo Access controls and compliance<ul><li>Separate and maintain clear boundaries between:</li></ul>o Core governed datasetso Downstream analytics/BI layersCloud &amp; Big Data Integration<ul><li>Integrate systems with:</li></ul>o Data lakes and large-scale data platforms<ul><li>Work with modern cloud ecosystems (AWS preferred):</li></ul>oo Data warehouse platforms (e.g., Redshift, Snowflake)<ul><li>Design cost-efficient and scalable data solutions</li></ul>Analytics Engineering &amp; Data Products<ul><li>Design and deliver data products used by:</li></ul>o Analystso Data scientistso Product teams<ul><li>Build reusable frameworks for:</li></ul>o Data transformationo Orchestrationo Feature engineering (ML readiness)<ul><li>Support advanced analytics and reporting use cases</li></ul>CI/CD &amp; DevOps for Data<ul><li>Implement CI/CD pipelines for data workflows</li><li>Automate:</li></ul>o Testingo Deploymento Validation<ul><li>Use version control systems (Git/GitHub)</li><li>Ensure:</li></ul>o High availabilityo Backup and recovery strategiesProgramming &amp; Tooling<ul><li>Develop solutions using:</li></ul>oo Python (automation, validation, tooling)<ul><li>Work with tools such as:</li></ul>o dbt (deep experience required)o DBeaver, Visual Studioo Orchestration tools (e.g., Dagster or similar)Leadership &amp; Collaboration<ul><li>Lead cross-functional technical initiatives</li><li>Mentor and guide junior to mid-level data engineers</li><li>Conduct:</li></ul>o Code reviewso Architecture discussionso Knowledge sharing sessions<ul><li>Collaborate with:</li></ul>o Engineering teamso Product managerso Business stakeholders<ul><li>Translate business requirements into scalable data solutions</li></ul>Strategic Impact<ul><li>Drive platform evolution and innovation</li><li>Identify opportunities for:</li></ul>o Performance improvementso Cost optimization (FinOps mindset)o Automation and scalability<ul><li>Influence organizational data strategy and roadmapRequired Qualifications</li><li>Bachelor&rsquo;s degree in computer science, Engineering, IT, or related field</li><li>4&ndash;5+ years of experience in data engineering or analytics engineering</li><li>Strong expertise in:</li></ul>o Data modeling (star schema, dimensional modeling)o SQL and performance tuningo ETL/ELT pipeline development<ul><li>Hands-on experience with:</li></ul>o Data warehousing and data lakeso Big data integrations<ul><li>Experience with:</li></ul>o Cloud platforms (AWS preferred)o Data quality, validation, and governance frameworks<ul><li>Strong understanding of:</li></ul>o System designo Scalable architecture<ul><li>Excellent communication and stakeholder management skills</li><li>Ability to work in agile, fast-paced environments</li><li>Eligibility to obtain security clearance (if required)</li></ul>Preferred Qualifications<ul><li>Experience with:</li></ul>o AWS services (Glue, Lambda, etc.)o Snowflake, Redshifto dbt (production-level deployments)<ul><li>Knowledge of:</li></ul>o Machine learning data pipelineso Certifications:o SQL Server, CDMP, MCSA, or similar<ul><li>Experience in:</li></ul>o Healthcare, defense, or regulated industries<ul><li>Familiarity with:</li></ul>o CI/CD for data systemso Data governance and FinOps practicesWhat Makes a Strong Candidate<ul><li>Thinks of systems, not just pipelines</li><li>Focuses on root-cause solutions, not temporary fixes</li><li>Balances:</li></ul>o Business valueo Scalabilityo Maintainability<ul><li>Strong ownership mindset with ability to lead initiatives end-to-end</li><li>Passion for building resilient, high-quality data platforms</li></ul>Job Type: Full-timePay: Rs250,000.00 - Rs350,000.00 per monthWork Location: In person

Lead Data Engineer

ibex

<div>
 We are seeking a highly motivated and responsible
 
 Data Engineer
 
 to join our dynamic team. This role requires hands-on experience in building scalable data pipelines, managing structured and unstructured databases, and supporting end-to-end data operations. The ideal candidate will bring strong problem-solving skills, a collaborative mindset, and a commitment to data excellence.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Design, develop, and manage reliable and scalable data pipelines.
 </li>
 <li>
 Clean, validate, and transform data from multiple sources for analytics and operational use.
 </li>
 <li>
 Work with large datasets and ensure high data quality and availability.
 </li>
 <li>
 Develop and maintain ETL workflows using standard tools and scripting.
 </li>
 <li>
 Automate data extraction, transformation, and loading processes across systems.
 </li>
 <li>
 Monitor and optimize performance of data workflows for speed and efficiency.
 </li>
 <li>
 Develop, maintain, and optimize complex SQL queries, stored procedures, functions, and views.
 </li>
 <li>
 Design and implement relational database schemas and indexing strategies.
 </li>
 <li>
 Ensure data integrity, security, and compliance within SQL Server environments.
 </li>
 <li>
 Work with MongoDB for storing and querying unstructured or semi-structured data.
 </li>
 <li>
 Design document-based data models and manage performance tuning for MongoDB.
 </li>
 <li>
 Handle replication and backup strategies where applicable.
 </li>
 <li>
 Analyze complex data requirements and translate them into efficient technical solutions.
 </li>
 <li>
 Identify data-related issues, perform root-cause analysis, and deliver timely resolutions.
 </li>
 <li>
 Work closely with data analysts, software engineers, and business stakeholders to understand requirements.
 </li>
 <li>
 Participate in code reviews, team planning sessions, and cross-functional meetings.
 </li>
 <li>
 Take ownership of assigned tasks with accountability and attention to detail.
 </li>
 <li>
 Exhibit a proactive approach to delivering solutions and supporting team goals.
 </li>
 <li>
 Contribute to architectural discussions and recommend improvements based on industry best practices.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Information Systems, or a related field.
 </li>
 <li>
 2&ndash;3 years of experience in data engineering or database development roles.
 </li>
 <li>
 Strong proficiency in SQL Server (T-SQL, indexing, optimization).
 </li>
 <li>
 Hands-on experience with MongoDB or other NoSQL technologies.
 </li>
 <li>
 Familiarity with data pipeline tools and ETL development.
 </li>
 <li>
 Working knowledge of Python or similar scripting languages.
 </li>
 <li>
 Understanding of data modeling, normalization, and data warehousing concepts.
 </li>
 <li>
 Strong analytical thinking and problem-solving skills.
 </li>
 <li>
 Excellent communication and teamwork abilities.
 </li>
 </ul>
</div>

Data Engineer, Tech

Datamatics Global Services Ltd

<div><h2 class="jobSectionHeader">Job Title: Senior Data Engineer (AWS)</h2>
Experience: 6&ndash;8 Years 
Location: Remote 
Industry: Retail / Data &amp; Analytics<h3 class="jobSectionHeader"> 
Job Summary</h3>
We are seeking highly skilled and innovative Senior Data Engineers (AWS) to join a dynamic team supporting advanced data initiatives. The ideal candidates will have strong hands-on experience in building scalable data pipelines, working with AWS data services, and delivering high-quality data solutions in fast-paced environments.
This role requires individuals who are problem-solvers, adaptable, and capable of working collaboratively within high-performing teams.<h3 class="jobSectionHeader">
Key Responsibilities</h3><ul><li>
Design, develop, and maintain scalable data pipelines using AWS services.</li><li>
Build and optimize ETL/ELT processes using AWS Glue and DBT (Data Build Tool).</li><li>
Manage and configure data workflows and orchestration within the Orion framework.</li><li>
Develop and maintain configuration files and ensure seamless integration across systems.</li><li>
Collaborate with data architects, analysts, and business stakeholders to deliver data solutions.</li><li>
Optimize data processing performance and ensure data quality and reliability.</li><li>
Work on data modeling, transformation, and warehousing solutions.</li><li>
Implement best practices for data governance, security, and compliance.</li><li>
Troubleshoot and resolve data-related issues across pipelines and infrastructure.</li><li>
Contribute to continuous improvement and innovation in data engineering practices.</li></ul><h3 class="jobSectionHeader">
Required Skills &amp; Expertise</h3><ul><li>
Strong experience with AWS ecosystem, including:<ul><li>
AWS Glue</li><li>
Amazon S3</li><li>
AWS Lambda</li><li>
Amazon Redshift / RDS</li></ul></li><li>
Hands-on expertise in DBT (Data Build Tool) for data transformation.</li><li>
Solid understanding of data pipeline architecture and ETL/ELT processes.</li><li>
Experience working with Orion framework and handling configuration-driven workflows.</li><li>
Good understanding of networking concepts within AWS environments (VPC, subnets, security groups).</li><li>
Proficiency in SQL and Python for data processing.</li><li>
Experience with version control systems (Git).</li><li>
Familiarity with CI/CD pipelines for data workflows.</li></ul><h3 class="jobSectionHeader">
Preferred Qualifications</h3><ul><li>
Experience in retail or supply chain data environments.</li><li>
Exposure to real-time data processing and streaming frameworks.</li><li>
Knowledge of data lake and lakehouse architectures.</li><li>
AWS certifications (e.g., AWS Certified Data Analytics or Solutions Architect).</li></ul><h3 class="jobSectionHeader">
Key Competencies</h3><ul><li>
Strong analytical and problem-solving skills</li><li>
Innovative mindset with a focus on continuous improvement</li><li>
Ability to work in high-performance, collaborative teams</li><li>
Excellent communication and stakeholder management skills</li><li>
Ownership and accountability for deliverables</li></ul>
soIkqs9cJc</div>

Senior Data Engineer (AWS)

CodeNinja

<div>About CodeNinja
CodeNinja is a full-stack AI delivery company that helps enterprises, governments, and software acquirers build and operate intelligence-driven systems for mission-critical workflows. We specialize in deploying AI into real operations&mdash;combining strong engineering fundamentals with AI-native delivery to create measurable value, resilience, and long-term ownership for our clients. Our global footprint and delivery model are supported by AI Labs, AI Pods, and Global Capability Centers, enabling teams to co-engineer scalable platforms across regions and time zones.
Role Purpose
Lead the ERP program&rsquo;s data strategy by ensuring data readiness, conceptual data modelling, reporting data sourcing, and structured data migration planning, enabling a reliable, unified data foundation across all modules.
Key Responsibilities<ul><li>Conduct comprehensive assessment of legacy data sources:</li></ul>
o Inventory, Maintenance (MRO), Procurement, HR, Technical Docs<ul><li>Identify:</li></ul>
o Data quality issues (duplicates, missing, inconsistencies)
o Data ownership and governance gaps
o Redundant/siloed datasets<ul><li>Define data cleansing and standardization approach</li><li>Produce Data Readiness Assessment Report</li><li>Define end-to-end Data Migration Strategy, including:</li></ul>
o Migration approach (phased, module-wise, or big-bang)
o Data prioritization (master data vs transactional vs historical)<ul><li>Develop Data Mapping Specifications:</li></ul>
o Legacy ERP field-level mappings
o Transformation rules and standardization logic
o Handling of missing/invalid data<ul><li>Define Data Cleansing &amp; Preparation Plan:</li></ul>
o Deduplication rules
o Data enrichment where required
o Validation checkpoints before migration<ul><li>Design Migration Execution Plan:</li></ul>
o Migration cycles (mock runs, dry runs, final cutover)
o Rollback strategy in case of failure
o Downtime and cutover planning<ul><li>Define Data Validation &amp; Reconciliation Framework:</li></ul>
o Pre-migration vs post-migration validation rules
o Reconciliation reports (counts, totals, relationships)
o Sign-off criteria for each module<ul><li>Produce key deliverables:</li></ul>
o Data Migration Plan
o Data Mapping Documents
o Data Validation &amp; Reconciliation Reports<ul><li>Identify and enable AI/ML use cases, such as:</li></ul>
o Predictive maintenance modeling
o Inventory demand forecasting
o Supplier performance analytics<ul><li>Leverage AI tools for:</li></ul>
o Data profiling and anomaly detection
o Data quality assessment and cleansing recommendations
o Advanced analytics and insights generation<ul><li>Define enterprise conceptual data model:</li></ul>
o Assets, Inventory, Work Orders, Suppliers, Workforce, Technical Docs<ul><li>Establish:</li></ul>
o Entity relationships
o Master data definitions
o Data standardization rules<ul><li>Support BI teams for dashboards and analytics</li><li>Align data models with business workflows</li><li>Ensure requirements are data-feasible and consistent</li></ul> 
Requirements 
3. Required Skills &amp; Experience
Mandatory<ul><li> 5 - 8 years in Data Analyst / Data Architecture roles</li><li>Experience in large-scale ERP or enterprise data transformation programs</li><li>Strong expertise in:</li></ul>
o Data modelling (conceptual &amp; logical)
o Data migration and cleansing
o Data warehousing and reporting
Technical Expertise<ul><li>Strong knowledge of:</li></ul>
o ETL processes and migration tools
o SQL and relational databases
o API-based integrations<ul><li>Experience with BI tools (Power BI, Tableau)</li></ul>
Preferred<ul><li>Experience in ERP &amp; Enterprise Data Management (logistics, manufacturing)</li><li>Exposure to:</li></ul>
o Maintenance (MRO) data
o Inventory systems
o Technical documentation repositories<ul><li>Demonstrated experience using AI/ML tools or platforms, such as:</li></ul>
o Data analysis and prediction tools
o AI-assisted data modeling or profiling tools<ul><li>Ability to translate data into AI-driven insights for decision-making</li></ul>
Why Join CodeNinja?<ul><li>
Work on impactful ERP transformation projects at enterprise scale
</li><li>Shape end-to-end data strategy, migration, and architecture
</li><li>Leverage AI/ML for advanced data insights and analytics
</li><li>Collaborate with cross-functional teams and drive business decisions
</li><li>Build scalable data models and governance frameworks
</li><li>Grow in a culture of innovation, ownership, and continuous learning</li></ul>
Equal Opportunity Statement
We are an equal opportunity employer and are committed to fostering an inclusive, diverse, and equitable workplace. We do not discriminate based on race, religion, gender, age, disability, nationality, marital status, or any other protected characteristic under applicable law. We encourage candidates from all backgrounds to apply. 
Benefits 
<ul><li>
Provident Fund</li><li>
Gym Membership
</li><li>Leaves as per the company policy
</li><li>Company-paid trips
</li><li>Easy Loan Facility for Employees
</li><li>Yearly increment
</li><li>Maternity Benefits (Leaves &amp; WFH)
</li><li>Health Insurance (Maternity covered) &ndash; includes spouse and parents (till age 80)</li></ul></div>

Data Engineer/Data Architect

Explore 636+ Data engineer in Lahore this April. Find roles across top companies and apply now to boost your career.

636 data engineer jobs In Lahore

Data Engineer

Data Engineer

Data Engineer

Lead Data Engineer

Data Engineer, Tech

Senior Data Engineer (AWS)

Data Engineer/Data Architect